This invention relates to automated reading systems and methods, and more particularly, to pattern and character recognition systems and methods including neural network-based character recognition systems and methods.
Computer technology has been used in a wide variety of situations, including business and commercial environments, to improve such areas as productivity, cost-effectiveness, quality, competitiveness, and customer service. Many companies have reduced or eliminated worker involvement in one or more operational aspects of the business by automating a portion or all of an operation.
A computer technology sub-field which has the potential to be useful in a plurality of settings is automated recognition of textual information. The field has been referred to generally as optical character recognition or OCR. In general, an OCR machine "reads" typewritten and/or handwritten characters and tries to determine which character from a fixed set of characters each of the typewritten and/or handwritten characters is intended to represent. Typically, the reading involves scanning a document on which the typewritten and/or handwritten characters appear and generating a binary or pixel (e.g., "black/white") image of the document, or selected sections of the document. The image typically is stored in computer memory and manipulated by data processing techniques to produce another binary image which is selected from a fixed set of binary images, each being representative of one of the characters of the fixed set of characters.
As used herein, a pixel is defined as an image information cell having either the binary state "on" or "off" (e.g., black or white, or 1 or 0).
After the typewritten and/or handwritten characters have been "recognized", the binary images of the recognized characters can be stored in computer memory (or on any kind of information storage device) and/or processed by data processing equipment just as any other binary data can be processed. The recognized characters also could be displayed on a computer display device to provide a user with a visual pixel image of the typewritten and/or handwritten characters read and recognized by the OCR machine.
While the recognition of typewritten characters is a difficult problem, the recognition of handwritten characters presents an even greater challenge. The reason for the complexity is that, in general, every person's handwriting is different.
Many industries such as the banking and financial industries would benefit from a handwriting recognition system capable of recognizing handwritten characters on documents including financial instruments such as checks. Banks, financial institutions, and other handlers of financial instruments such as checks typically use automated equipment somewhere in the check handling process, however human operators sitting at keyboard entry devices are employed to read and enter the "courtesy amount" into a computer system. For example, an automatic check feeder can be used to continually move checks from a storage location to a position in front of the human operator to allow the operator to enter manually the courtesy amounts of the checks into the computer system via the keyboard entry device. (The courtesy amount on a check is the amount of the check, as written by the drawer of the check in Arabic numerals in a small box on the face of the check.)
A character recognition system which can read and recognize a variety of characters, including handwritten characters such as handwritten numerals, on documents without substantial human intervention is desired.